It is well known that in an MIMO system, knowing the spatial correlation matrix of transmit antennas at a transmitting end can significantly improve system performance. In practice, the correlation matrix cannot be known in advance. For instance, for a Frequency-Division Duplex (FDD) system, it is necessary to let the transmitting end know the approximation of the correlation matrix via quantization and feedback. Hence, the feedback overhead and quantization precision are main concerns for correlation matrix feedback in a MIMO system.
In discussions of LTE-A, it is proposed to feed back multiple eigenvectors quantized with multiple Discrete Fourier Transform (DFT) vector codebooks and the corresponding eigenvalues quantized with a uniform scalar codebook, and to reconstruct the correlation matrix at the transmitting end with the quantized eigenvectors and eigenvalues. Marwell proposed to feedback two or four real scalars quantized with a uniform scalar codebook and to reconstruct the correlation matrix at the transmitting end with the quantized scalars. These feedback solutions based on eigenvectors and based on scalars have not yet used the matrix structure of the spatial correlation matrix and a special antenna configuration, for example, uniform linear array (ULA) antennas, and thus the amount of data to be fed back is still large, which causes a higher feedback overhead.
Currently, for use of closely-spaced ULA antennas as a typical antenna configuration, there has not been provided a corresponding correlation-matrix feedback method. Since the spacing between two antennas in the closely-spaced ULA antennas is very small, the correlation matrix thereof is characterized in that all diagonal entries are 1. For this special antenna configuration, there is a need to design a corresponding correlation matrix feedback method and a codebook for the quantization and feedback of the correlation matrix so as to achieve excellent system performance with a smaller feedback overhead and lower complexity.